Ditlevsenmartin8722
The NF1 gene encodes neurofibromin, which is one of the primary negative regulatory factors of the Ras protein. Neurofibromin stimulates the GTPase activity of Ras to convert it from an active GTP-bound form to its inactive GDP-bound form through its GTPase activating protein-related domain (GRD). Therefore, neurofibromin serves as a shutdown signal for all vertebrate RAS GTPases. NF1 mutations cause a resultant decrease in neurofibromin expression, which has been detected in many human malignancies, including NSCLC, breast cancer and so on. NF1 mutations are associated with the underlying mechanisms of treatment resistance discovered in multiple malignancies. This paper reviews the possible mechanisms of NF1 mutation-induced therapeutic resistance to chemotherapy, endocrine therapy and targeted therapy in malignancies. Then, we further discuss advancements in targeted therapy for NF1-mutated malignant tumors. In addition, therapies targeting the downstream molecules of NF1 might be potential novel strategies for the treatment of advanced malignancies.
Glioblastoma multiforme (GBM) is the most malignant tumor in human brain, with highly heterogeneity among different patients. Age could function as an incidence and prognosis risk factor for many tumors.
A series of bioinformatic experiments were conducted to evaluate the differences of incidence, differential expressed genes, enriched pathways with the data from Surveillance, Epidemiology, and End Results (SEER) program, the cancer genome atlas (TCGA) and Chinese glioma genome atlas (CGGA) project.
We discovered in our present study that distinct difference of incidence and prognosis of different aged GBM patients. By a series of bioinformatic method, we found that the tumor associated fibroblasts (TAFs) was the most crucial tumor microenvironment (TME) component that led to this phenomenon. Epithelial-mesenchymal transition (EMT) could be the mechanism by which TAFs regulate the progression of GBM.
We have proposed a close correlation between age and GBM incidence and prognosis, and propose the underlying mechanism behind this correlation by mining different databases, which laid the foundation for future research.
We have proposed a close correlation between age and GBM incidence and prognosis, and propose the underlying mechanism behind this correlation by mining different databases, which laid the foundation for future research.
It is estimated by the year 2050, 80% of the global elderly population will be from the low-and middle income countries. Elderly care requires health workers with skills associated with an understanding of the biological, psychological, social and cultural theories related to aging. Nurses with better knowledge, skills and positive attitudes towards elderly care are highly needed and critically important for better healthcare and wellbeing of the elderly population. Therefore the objective of this study was to assess the level of knowledge and attitude of nursing students towards elderly care in Zanzibar Island.
A cross-sectional study was conducted in Zanzibar involving three out of five nursing training institutions. Participants were selected by systematic random sampling. Facts on Aging Quiz 2 and Kogan's Attitudes Toward Old People scale were used to assess the level of knowledge and attitude towards elderly care among the students respectively. Simple and multivariable logistic regressions were appldge shown in the study suggests for further research on adequacy of nursing curriculum and/or its implementation.
This study has shown that the majority of nursing students in Zanzibar have positive attitude but poor level of knowledge towards elderly care. The current findings have demonstrated that past experience with an elderly person can help in influencing good knowledge and shaping positive attitudes towards elderly care. Low level of knowledge shown in the study suggests for further research on adequacy of nursing curriculum and/or its implementation.
Worldwide, studies show a relationship between nurses' health and some work environment factors; however, data on nurses' health and self-perceived workload and nursing task allocation are lacking, particularly for Lebanese nurses. We assessed the relationship of several work environment factors overall workload and specific temporal, physical, mental, effort, frustration, and performance demands (NASA Task Load Index), staffing resources and adequacy and leadership (Practice Environment Scale of Nursing Work Index), teamwork climate (Safety Attitudes Questionnaire), and nursing task allocation (Basel Extent of Rationing of Nursing Care)) with self-reported musculoskeletal, cardiovascular, skin, and mental health diseases (Work Ability Index) and emotional exhaustion (Maslach Burnout Inventory) among Lebanese nurses.
A cross-sectional self-report survey was distributed to all 289 registered nurses (RNs) in the medical, surgical, and pediatric units in two Lebanese university-affiliated hospitals; 170 RNs alth burden and co-morbidity among Lebanese RNs and highlight the value of comprehensive approaches that can simultaneously improve several work environment factors (namely self-perceived workload, teamwork,, resources, and nursing task allocation) to reduce this burden.
Results show elevated health burden and co-morbidity among Lebanese RNs and highlight the value of comprehensive approaches that can simultaneously improve several work environment factors (namely self-perceived workload, teamwork,, resources, and nursing task allocation) to reduce this burden.Triboelectric nanogenerators (TENGs) that enable the conversion of a given mechanical energy into electrical energy at high efficiency have been very important in practice. Since the given mechanical energy is involuntarily converted to secondary energy sources (light, heat, and sound during triboelectrification), the significant amount of energy being converted is lost. Various studies have thus been continuously carried out to overcome this issue. Selleck TL13-112 Since the first TENGs found in 2012, various developments in TENGs have been made (1) the mechanical-electrical energy conversion characteristics of potential organic/inorganic material groups have been introduced, (2) the integration into the device structure considering the diversity of mechanical energy, and (3) user friendly and industrial application platforms have been aggressively studied. Despite the remarkable progress and improvement of TENGs, their mechanical-electrical conversion efficiency is still quite low. We therefore need to discover and develop materials that can be converted to improve efficiency.
